Tools for World Wide Web based legal decision support systems

  • Authors:

  • Andrew Stranieri;John Yearwood;John Zeleznikow

  • Affiliations:

  • Donald Berman, Laboratory for Information Technology and Law, La Trobe University, Bundoora Australia;School of Information Technology and Mathematical Sciences, University of Ballarat, Victoria, Australia;Donald Berman, Laboratory for Information Technology and Law, La Trobe University, Bundoora Australia and Centre for Forensic Statistics and Legal Reasoning, Faculty of Law, University of Edinburg ...

  • Venue:
  • Proceedings of the 8th international conference on Artificial intelligence and law
  • Year:
  • 2001

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Abstract

The majority of legal knowledge based systems (LKBS) in commercial use are rule based and target domains of law characterized by large and complex statutes where modelling discretion is not a central concern. Furthermore, to date, few LKBS execute on the World Wide Web. Despite this, LKBS designed for a web environment can make law more universally accessible and transparent. Tools required to facilitate the development of web based systems include a web based expert system shell, conceptual tools that allow for the identification of appropriate domains for web implementation, modeling tools for discretionary domains and architectures for virtual discourse. We present a shell called WebShell that uses two knowledge modelling techniques; decision trees for procedural type tasks and argument trees for tasks that are more discretionary. Rather than translate decision tree knowledge into rules for a conventional inference engine, we map the decision trees into sets we call sequence transition networks. These sets can readily be stored in relational database format in a way that simplifies the inference engine design. Although WebShell facilitates the deployment of LKBS in a web environment, it does not encourage negotiation and virtual discourse. An argumentation shell program, Argument Developer is presented that encourages participants in a virtual discursive community to understand each other's perspectives and reach decisions by consensus.